Deepflare
Deepflare is dedicated to accelerating vaccine discovery and biotech innovation through AI and machine learning. Their mission is to make biology more predictable, programmable, and cost-efficient, focusing on areas such as vaccine design, protein engineering, and cell therapies. They aim to unlock the potential of mRNA technology and improve drug development pipelines, ultimately entering a new age of therapeutic discovery.
Industries
Nr. of Employees
small (1-50)
Deepflare
Products
Multi-module mRNA vaccine support system (CovidGenomics project)
A multi-module system to support mRNA vaccine development including modules for viral evolution prediction, peptide and epitope selection, and classification of peptides by mutation resilience over a one-year horizon.
Multi-module mRNA vaccine support system (CovidGenomics project)
A multi-module system to support mRNA vaccine development including modules for viral evolution prediction, peptide and epitope selection, and classification of peptides by mutation resilience over a one-year horizon.
Services
Computational design and prioritization of vaccine constructs using structure-aware modelling and immunogenicity scoring for preclinical candidate selection.
Computational pipeline to predict protein structures, assess stability and binding, and iteratively redesign sequences to meet functional objectives.
Design, build, validate, and deploy deep learning models for protein data and preclinical study recommendation systems, supported by MLOps practices.
Analytics services that ingest multivariate CQAs (including images and bioreactor telemetry) and donor variables to optimize manufacturing processes and reduce batch failure risk.
Predictive analysis of viral evolution and identification of peptides resilient to likely future mutations to inform long-horizon vaccine design.
Computational design and prioritization of vaccine constructs using structure-aware modelling and immunogenicity scoring for preclinical candidate selection.
Computational pipeline to predict protein structures, assess stability and binding, and iteratively redesign sequences to meet functional objectives.
Design, build, validate, and deploy deep learning models for protein data and preclinical study recommendation systems, supported by MLOps practices.
Analytics services that ingest multivariate CQAs (including images and bioreactor telemetry) and donor variables to optimize manufacturing processes and reduce batch failure risk.
Predictive analysis of viral evolution and identification of peptides resilient to likely future mutations to inform long-horizon vaccine design.
Expertise Areas
- Vaccine design and mRNA vaccine development
- Protein engineering and structure-based design
- Computational immunology and epitope prediction
- Viral evolution modelling
Key Technologies
- Deep learning for protein data
- Protein 3D structure prediction
- Binding affinity prediction
- Immunogenicity modelling